Performance of Interpolated Histogram of Oriented Gradients on the Feature Calculation of SIFT

Autor:	OZTURK, A., CAYIROGLU, I.
Jazyk:	angličtina
Rok vydání:	2022
Předmět:	image processing computer vision image analysis feature extraction object detection Electrical engineering. Electronics. Nuclear engineering TK1-9971 Computer engineering. Computer hardware TK7885-7895
Zdroj:	Advances in Electrical and Computer Engineering, Vol 22, Iss 3, Pp 87-94 (2022)
Druh dokumentu:	article
ISSN:	1582-7445 1844-7600
DOI:	10.4316/AECE.2022.03010
Popis:	Scale Invariant Feature Transform (SIFT) is the most dominant and robust object detection algorithm. It utilizes the Histogram of Oriented Gradients (HOG) method for feature computation. HOG is applied with trilinear interpolation to gain performance improvement. This paper examines the effect of interpolation on the performance of SIFT on both OXFORD and HPatches datasets. The various algorithms of interpolation for HOG, and the spatial binning process algorithm, are presented here. The performance is evaluated with Intersection Over Union, Correct Match Percentage, as well as the execution time of the algorithms. Moreover, we used the multiplication of the Intersection Over Union and Correct Match Percentage to take advantage of both metrics. It was observed that the interpolation did not significantly affect the performance of the SIFT.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/1a0d52f77dc549cabc9f2c5472bdea77 Zobrazit plný text záznamu View record in DOAJ